SSAS: What is Linked Dimension ?

In SQL Server Analysis Services (SSAS), Linked Dimension is a dimension which is existed in other analysis services DB. It may exist in same or different server. it helps the user to keep the common dimension in multiple database.

What is Conformed dimension?

Conformed dimension is a dimension that has a single meaning or content throught datawarehouse.we can use it accross the fact tables


Example: Time, Product, Staff Dimensions are Conformed dimension, it is shared across multiple fact tables.

What is Role Playing dimension?

Role Playing dimension is a dimension, it can play different roles in a fact table depending on the context.

For example: Date dimension

Date dimension can be used for ordered date, shipping date, shipment date, and invoice date, etc., in an order line fact.

In the data warehouse, you will have a single dimension table for the dates. You will have multiple warehouse foreign key from the fact table to teh same dimension.

What is junk dimension?

A junk dimension is a collection of random transcational codes flags and text attributes that are unrelated to any particular dimension.The junk dimension is simply a structure that provides the convienent place to store the junk dimension.

Operational Data Store Vs Data warehouse

Operational Data Store(ODS)	Data warehouse
ODS is an Online integration of data	Typically it won't provide online Information.  It provides offline  data.
ODS is used, when a system's data is required to access from some other systems immediately. Ex: records updated from various section, data is lying in different DB, of Hospital is required while billing or some other activities	It is used while making decisions from past and present data(bit old, may be data taken from hours or days back)
ODS is centralized repository of data for online operational use	This is Non-Operational use

What is Data warehouse?

Data warehouse is repository of data, which are collected from many sources like transactional database or old backup data, etc., and then filtered, cleansed, transformed the data for the purpose of analyzing, decision making and reporting.